When operating software doesn’t require a lot of training, users of that software are likely to be poorly trained. This is an adverse selection issue. Researchers who care about statistics enough should have gravitated toward R at some point. I also trust results produced using R, not because it is better software, but because it is difficult to learn. The software is not causing you to be a better scientist, but better scientists will be using it.

You can also read his list a of what your choice of statistical software pacakge (SAS, SPSS, Matlab, Julia and more) says about you, at the link below.

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Although I agree with most of what is said in this essay, I would like to point out that most of us social scientists were trained to use SPSS back in the old days. For many of us using SPSS is simply a carry-over from the days of mainframe computers.

This phenomenon was observed at least as early as Lotus 1-2-3, and made manifest with Excel. Barely, or un-, trained "support staff" became quantitative analysts, thanks to the Spreadsheet Mind Meld. We continue to pay the price. I've always suspected that The Great Recession resulted from the empowerment of the clueless.

For the record, I started with BMD-P, and have used virtually every package save Stata since. R is my 7% solution of choice these days.